HINT A Hierarchical Index for Intervals in Main Memory

Indexing intervals is a fundamental problem, finding a wide range of applications . Recent work on managing large collections of intervals in mainmemory focused on overlap joins and temporal aggregation problems . In thispaper, we propose novel and efficient in-memory indexing techniques for intervals .…

A Prioritized Trajectory Planning Algorithm for Connected and Automated Vehicle Mandatory Lane Changes

We introduce a prioritized system-optimal algorithm for mandatory lane change(MLC) behavior of connected and automated vehicles (CAV) from a dedicated lane . Our approach outperforms the traditional gap acceptance model . Our experiments on synthetic data show that the proposed algorithm improves the traffic networkefficiency by attaining higher speeds in the dedicated lane and earlier MLCpositions while ensuring a low computational time .…

ManipulaTHOR A Framework for Visual Object Manipulation

The domain of Embodied AI has recently witnessed substantial progress in navigating agents within their environments . We propose a framework for object manipulation builtupon the physics-enabled, visually rich AI2-THOR framework . ArmPointNav offers new challenges including 3D obstacle avoidance, manipulating objects in thepresence of occlusion, and multi-object manipulation that necessitates longterm planning .…

Restoring degraded speech via a modified diffusion model

DiffWave has shown state-of-the-artsynthesized speech quality and relatively shorter waveform generation times,with only a small set of parameters . We replace the mel-spectrum upsampler in DiffWave with a deep CNN upsamplator . The model is trained using the original speech waveform, but conditioned on the degraded speechmel-spectrums .…

The Density Fingerprint of a Periodic Point Set

Fingerprinth is a fast algorithm based on Brillouin zones and related inclusion-exclusionformulae . We prove invariance under isometries,continuity, and completeness in the generic case . The proof of continuity integratesmethods from discrete geometry and lattice theory . We have implemented the algorithm and describe its application tocrystal structure prediction .…

Model Driven Deep Learning Based Channel Estimation and Feedback for Millimeter Wave Massive Hybrid MIMO Systems

This paper proposes a model-driven deep learning (MDDL)-based channelestimation and feedback scheme for wideband millimeter-wave (mmWave) massivehybrid multiple-input multiple- input multiple-output (MIMO) systems . The angle-delay domain channels’ sparsity is exploited for reducing the overhead for estimating the high-dimensional channels from a limited number of radio frequency (RF) chains at the base station .…

Multi point Coordination in Massive MIMO Systems with Sectorized Antennas

Non-cooperative cellular massive MIMO, combined with power control, is knownto lead to significant improvements in per-user throughput compared with conventional LTE technology . We demonstrate that employing sectorizedantenna elements mitigates the detrimental effects of pilot contamination by rejecting a portion of interfering pilots in the spatial domain during channelestimation phase .…

Identifying Actions for Sound Event Classification

In Psychology, actions are paramount for humans to perceive and separatesound events . We propose a new Psychology-inspired approach for SEC that includes identification of actions via human listeners . We used crowdsourcing to have listeners identify 20 actions that in isolation or in combination may have produced any of the 50 sound events in the well-studied dataset ESC-50 .…

Topological Simplifications of Hypergraphs

We study hypergraph visualization via its topological simplification . In simplifying a hypergraph, we allowvertices to be combined if they belong to almost the same set of hyperedges . Our proposed approaches are general, mathematically justifiable, and they putvertex simplification and hyperedge simplification in a unifying framework.…

Voice2Mesh Cross Modal 3D Face Model Generation from Voices

Previous works for cross-modal facesynthesis study image generation from voices . However, image synthesis includesvariations such as hairstyles, backgrounds, and facial textures, that arearguably irrelevant to voice . Weinstead investigate the ability to reconstruct 3D faces to concentrate on onlygeometry, which is more physiologically grounded .…

QCSP on Reflexive Tournaments

We give a complexity dichotomy for the Quantified Constraint SatisfactionProblem QCSP(H) when H is a reflexive tournament . We prove that if H has both its initialand final strongly connected component (possibly equal) of size 1, then QCSP is NP-hard .…

Label Synchronous Speech to Text Alignment for ASR Using Forward and Backward Transformers

The speech-to-text alignment is a problem of splitting long audio recordings with un-aligned transcripts into utterance-wise pairs of speech and text . Unlike conventional methods, the proposed method re-defines the problem as a label-synchronous text mapping problem . Thisenables an accurate alignment benefiting from the strong inference ability of the state-of-the-art attention-based encoder-decoder models, which cannot be applied to the conventional methods .…

Wireless Sensing With Deep Spectrogram Network and Primitive Based Autoregressive Hybrid Channel Model

Human motion recognition (HMR) based on wireless sensing is a low-costtechnique for scene understanding . Current HMR systems adopt support vectormachines (SVMs) and convolutional neural networks (CNNs) to classify radarsignals . On the other hand, training a machinelearning model requires a large dataset, but data gathering from experiment iscost-expensive and time-consuming .…

Acyclic Star and Injective Colouring Bounding the Diameter

We examine the effect of bounding the diameter for well-studied variants of the Colouring problem . A colouring is acyclic, star, or injective if any twocolour classes induce a forest, star forest or disjoint union of vertices andedges . The corresponding decision problems are Acyclic Colouring,Star Colouring and Injective Colouring .…

Efficient Sparse Coding using Hierarchical Riemannian Pursuit

Sparse coding is a class of unsupervised methods for learning a sparserepresentation of the input data in the form of a linear combination of adictionary and a sparse code . Initial non-convexapproaches learn the dictionary in the sparse coding problem sequentially in anatom-by-atom manner, which leads to a long execution time .…

Three Dimensional Mesh Steganography and Steganalysis A Review

Three-dimensional (3-D) meshes are commonly used to represent virtualsurfaces and volumes . Over the past decade, 3-D meshes have emerged in industrial, medical, and entertainment applications . We propose a new taxonomy of steganographic algorithms with four categories: 1) two-state domain, 2- LSB domain, 3) permutation domain, 4) transform domain .…

Model aided Deep Reinforcement Learning for Sample efficient UAV Trajectory Design in IoT Networks

Deep Reinforcement Learning (DRL) has become a prominent paradigm to designtrajectories for autonomous unmanned aerial vehicles . We propose a model-aided deep Q-learning approach that, in contrastto previous work, requires a minimum of expensive training data samples and isable to guide a flight-time restricted UAV on a data harvesting mission without prior knowledge of wireless channel characteristics and limited knowledge of node locations .…

What s The Context Long Context NLM Adaptation for ASR Rescoring in Conversational Agents

Neural Language Models (NLM) consistently outperform n-gram language models and NLMs that use limited context . We propose the use of attention layer over lexicalmetadata to improve feature based augmentation . We adapt ourcontextual NLM towards user provided on-the-fly speech patterns by leveragingencodings from a large pre-trained masked language model and performing fusion with a Transformer-XL based NLM .…

Stable Nonlinear and IQ Imbalance RF Fingerprint for Wireless OFDM Devices

An estimation method of Radio Frequency fingerprint (RFF) based on the physical hardware properties of the nonlinearity and in-phase and quadrature(IQ) imbalance of the transmitter is proposed for the authentication of wireless orthogonal frequency division multiplexing (OFDM) devices . The proposed RFfingerprinting method is helpful for the high-strength authentication of theOFDM communication devices with subtle differences from the same model and sameseries .…

Towards Exploratory Landscape Analysis for Large scale Optimization A Dimensionality Reduction Framework

Little is known about the scalability of the ELA approach for large-scale optimization . Two important feature classes (ela_level and ela_meta) cannot be applied to optimization due to their high computational cost . Adimensionality reduction framework proposes a framework that computes features in a reducedlower-dimensional space than the original solution space .…

Lossless Compression with Latent Variable Models

We develop a simple and elegant method for lossless compression using latentvariable models . The method involves interleaving encode and decode steps, andachieves an optimal rate when compressing batches of data . We demonstrate it firstly on the MNIST test set, showing that state-of-the-art losslesscompression is possible using a small variational autoencoder (VAE) model .…

On reduction and normalization in the computational core

We study the reduction in a lambda-calculus derived from Moggi’s computational core . The reduction relationconsists of rules obtained by orienting three monadic laws . We investigate the central notions of returning a value versus having a normal form, and address the question of normalizing strategies .…

A convergent numerical scheme for a model of liquid crystal dynamics subjected to an electric field

We present a convergent and constraint-preserving numerical discretization of a mathematical model for the dynamics of a liquid crystal subjected to anelectric field . This model can be derived from the Oseen-Frank director fieldtheory . We show that the method is stable even when singularities develop, and predictions about the alignment of the director field with the electric field are confirmed .…

On the Width of Regular Classes of Finite Structures

In this work, we introduce the notion of decisional width of a finiterelational structure . We also introduce the idea of decisionality of a regular class offinite structures . Our main result states that given a first-order formula, and a finite automaton F over a suitablealphabet B, one can decide in time f (f) whether some {\tau}-structure in C satisfies {\psi}.…

Carbon Emissions and Large Neural Network Training

The computation demand for machine learning (ML) has grown rapidly recently, which comes with a number of costs . We calculate the energy use and carbon footprint of several recent large models-T5, Meena, GShard, Switch Transformer, andGPT-3-and refine earlier estimates for the neural architecture search that found Evolved Transformer .…

FD JCAS Techniques for mmWave HetNets Ginibre Point Process Modeling and Analysis

Co-design of full-duplex (FD) radio with jointcommunication and radar sensing (JCAS) techniques in millimeter-wave (mmWave)heterogeneous networks (HetNets) Spectral co-existence of radar and communication systems causes mutual interference between the two systems . Focusing on thedetection performance, we propose a cooperative detection technique, whichexploits the sensing information from multiple base stations (BSs) In real-world network scenarios, the locations of the BSsare spatially correlated, exhibiting a repulsive behavior .…

Game Theory to Study Interactions between Mobility Stakeholders

Increasing urbanization and exacerbation of sustainability goals threaten theoperational efficiency of current transportation systems . Rise of private, profit-maximizing Mobility Service Providers leveragingpublic resources, such as ride-hailing companies, entangles current regulationschemes . In this paper, we provide a game-theoretic framework to study interactions between stakeholders of the mobility ecosystem, modeling regulatory aspectssuch as taxes and public transport prices, as well as operational matters forMobility Services Providers such as pricing strategy, fleet sizing, and vehicledesign .…

Reduced order modeling of LPV systems in the Loewner framework

We propose a model reduction method for LPV systems . We consider LPV state-space representations with an affine dependence on the schedulingvariables . The main idea behind the proposed method is to compute the reducedorder model in such a manner that its frequency domain transfer function matches with that of the original model for some frequencies .…

Macroeconomic forecasting with statistically validated knowledge graphs

This study leverages narrative from global newspapers to construct theme-based knowledge graphs about world events . It shows that featuresextracted from such graphs improve forecasts of industrial production in threelarge economies compared to a number of benchmarks . The theme categories “disease” and “economic” have the strongest predictive power during the time period that we consider .…

Predictive analytics using Social Big Data and machine learning

The ever-increase in the quality and quantity of data generated fromday-to-day businesses operations in conjunction with the continuously importedrelated social data have made the traditional statistical approaches inadequateto tackle such data floods . This chapter sheds the light on coreaspects that lay the foundations for social big data analytics .…